Stand Up a Data Platform for a Mobility-Data Startup's First ML Model
Overview
What this challenge is about.
Stand Up a Data Platform for a Mobility-Data Startup's First ML Model. Expert-level challenge in code. Writing production code that solves real engineering p...
The Brief
What you'll do, and what you'll demonstrate.
Stand up a working data platform slice (streaming + batch + feature store + training job) for a mobility-data startup's first ML model.
This is not a coding exercise. It is the work a software engineer does between a Jira ticket and a merged PR. That distinction matters to every hiring manager who has seen candidates solve LeetCode problems and none who have shipped production code under real constraints.
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
Earning criteria — what you'll demonstrate
- Design a data platform across streaming, batch, and feature serving layers
- Implement infrastructure-as-code for reproducible environments
- Operate a feature store as the contract between data and ML
- Hand off a platform with documentation that survives without you
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
AI Software Engineering Group Project
Master · Capstone
Strong alignment
This challenge maps to AI Software Engineering Group Project at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Data Engineering
Design and build pipelines that collect, transform, and deliver reliable data at scale.
- Streaming Ingestion
Apply streaming ingestion to solve real industry problems and demonstrate production-level capability.
- Feature Store
Apply feature store to solve real industry problems and demonstrate production-level capability.
- Infrastructure As Code
Apply infrastructure as code to solve real industry problems and demonstrate production-level capability.
- Ci Cd
Apply ci cd to solve real industry problems and demonstrate production-level capability.
- Team Collaboration
Apply team collaboration to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
MLOps Engineer
Infrastructure-as-code plus feature-store contracts are bread-and-butter MLOps responsibilities.
This challenge sharpens
- infrastructure-as-code
- feature-store
- ci-cd
Machine Learning Engineer
Wiring a sample training job into the platform mirrors the MLE's daily integration work.
This challenge sharpens
- feature-store
- ci-cd
- team-collaboration